Yanyan Shen (沈艳艳)

Associate Professor with Tenure
Department of Computer Science and Engineering
Shanghai Jiao Tong University

Email: shenyy [AT] sjtu.edu.cn
Data Driven Software Engineering Lab

Bio

Yanyan is currently a tenured associate professor at the Department of Computer Science and Engineering, Shanghai Jiao Tong University (SJTU). She received her bachelor degree from Peking University (PKU), and obtained her doctoral degree from National University of Singapore (NUS). Her broad research interests include: databases, data mining and machine learning. She focuses on developing efficient and automated solutions to facilitate data analytics in various data-driven application domains including finance, e-commerce, etc.

Yanyan has won a few awards, including ICDE 2023 best paper award, PVLDB 2022 best research paper award, DASFAA 2019 best paper runner-up, APWeb-WAIM 2018 best student paper award, etc. She has served as a PC member of top international conferences such as SIGMOD, PVLDB, ICDE, KDD and has been selected as VLDB 2023 and 2024 Distinguished Associate Editor, VLDB 2019 Distinguished Reviewer, ICDE 2019 Outstanding Reviewer. She has been invited to serve as Associate Editor of IEEE TKDE, VLDB Journal, and PVLDB 2023/2024.

Research Interests

• DB for AI / DB x AI
• Complex Data Analytics
• Responsible Machine Learning

Recent Publications

See full publications in Google Scholar. The code repositories for the recent papers are available here.

• Yanyan Shen, et al. Efficient Training of Graph Neural Networks on Large Graphs tutorial. PVLDB, 2024.
• Shihong Gao, et al. SIMPLE: Efficient Temporal Graph Neural Network Training at Scale with Dynamic Data Placement. In Proceedings of the 2024 International Conference on Management of Data (SIGMOD), 2024.
• Jingzhi Fang, et al. STile: Searching Hybrid Sparse Formats for Sparse Deep Learning Operators Automatically. In Proceedings of the 2024 International Conference on Management of Data (SIGMOD), 2024.
• Lifan Zhao, Yanyan Shen. Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators. In Proceedings of the 12th International Conference on Learning Representations (ICLR), 2024.
• Jiale Deng, Yanyan Shen. Self-Interpretable Graph Learning with Sufficient and Necessary Explanations. In Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI), 2024. (accept rate=2342/9862=23.75\%)
• Jinyong Fan, Yanyan Shen. StockMixer: A Simple yet Strong MLP-based Architecture for Stock Price Forecasting. In Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI), 2024.
• Tong Li, et al. MASTER: Market-Guided Stock Transformer for Stock Price Forecasting. In Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI), 2024.
• Shihong Gao, et al. ETC: Efficient Training of Temporal Graph Neural Networks over Large-scale Dynamic Graphs. In Proceedings of the VLDB Endowment (PVLDB), 2024.
• Lifan Zhao, Shuming Kong, Yanyan Shen. DoubleAdapt: A Meta-learning Approach to Incremental Learning for Stock Trend Forecasting. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023. (research track, accept rate=313/1416=22.1%)
• Zhikai Wang, Yanyan Shen, et al. Feature Staleness Aware Incremental Learning for CTR Prediction. In Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI), 2023. (accept rate=15%)
• Tong Li, Jiale Deng, Yanyan Shen, Luyu Qiu, Yongxiang Huang, Caleb Chen Cao. Towards Fine-grained Explainability for Heterogeneous Graph Neural Network. In Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI), 2023. (accept rate=1721/8777=19.6%)
• Yiming Li, Yanyan Shen, et al. Orca: Scalable Temporal Graph Neural Networks Training with Theoretical Guarantees. In Proceedings of the 2023 International Conference on Management of Data (SIGMOD), 2023.
• Xin Zhang, Yanyan Shen, et al. DUCATI: A Dual-Cache Training System for Graph Neural Networks on Giant Graphs with GPU. In Proceedings of the 2023 International Conference on Management of Data (SIGMOD), 2023.
• Jia Li, Yanyan Shen, et al. SSIN: Self-Supervised Learning for Rainfall Spatial Interpolation. In Proceedings of the 2023 International Conference on Management of Data (SIGMOD), 2023.
• Yiming Li, Yanyan Shen, et al. Zebra: When Temporal Graph Neural Networks Meet Temporal Personalized PageRank. In Proceedings of the VLDB Endowment (PVLDB), 2023.
• Zhikai Wang, Yanyan Shen. Incremental Learning for Multi-Interest Sequential Recommendation. In Proceedings of the 39th IEEE International Conference on Data Engineering (ICDE), 2023.
• Shuming Kong, Yanyan Shen, et al. Resolving Training Biases via Influence-based Data Relabeling. In Proceedings of the 10th International Conference on Learning Representations (ICLR), 2022. (oral, accept rate = 54/3391)
• Shuming Kong, Weiyu Cheng, Yanyan Shen, Linpeng Huang. AutoSrh: An Embedding Dimensionality Search Framework for Tabular Data Prediction. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022.
• Yanyan Shen, Lifan Zhao, et al. RESUS: Warm-Up Cold Users via Meta-Learning Residual User Preferences in CTR Prediction. ACM Transactions on Information Systems (TOIS), 2022.
• Yiming Li, Yanyan Shen, et al. Camel: Managing Data for Efficient Stream Learning. In Proceedings of the 2022 International Conference on Management of Data (SIGMOD), 2022.
• Qiyu Liu, Yanyan Shen, et al. LHI: A Learned Hamming Space Index Framework for Efficient Similarity Search. In Proceedings of the 2022 International Conference on Management of Data (SIGMOD), 2022.
• Jingzhi Fang, Yanyan Shen, et al. ETO: Accelerating Optimization of DNN Operators by High-Performance Tensor Program Reuse. In Proceedings of the VLDB Endowment (PVLDB), 2022.
• Jingshu Peng, et al. Sancus: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks. In Proceedings of the VLDB Endowment (PVLDB), 2022.
• Runjin Chen, Yanyan Shen, et al. GNEM: A Generic One-to-Set Neural Entity Matching Framework. In Proceedings of the Web Conference (TheWebConf), 2021.
• Qiyu Liu, Yanyan Shen, et al. LHist: Towards Learning Multi-dimensional Histogram for Massive Spatial Data. In Proceedings of the 37th IEEE International Conference on Data Engineering (ICDE), 2021.
• Yiming Li, Yanyan Shen, et al. Palette: Towards Multi-source Model Selection and Ensemble for Reuse. In Proceedings of the 37th IEEE International Conference on Data Engineering (ICDE), 2021.
• Jingzhi Fang, Yanyan Shen, et al. Optimizing DNN Computation Graph using Graph Substitutions. In Proceedings of the VLDB Endowment (PVLDB), 2020.
• Qiyu Liu, Libin Zheng, Yanyan Shen, et al. Stable Learned Bloom Filters for Data Streams. In Proceedings of the VLDB Endowment (PVLDB), 2020.
• Weiyu Cheng, Yanyan Shen, et al. Adaptive Factorization Network: Learning Adaptive-Order Feature Interactions. In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI), 2020. (accept rate=1591/7737)

Professional Service

Journal Associate Editor

• IEEE Transactions on Knowledge and Data Engineering (TKDE)
• VLDB Journal (VLDBJ)

Journal Guest Editor

• VLDB Journal (Special Issue on Data Science for Responsible Data Management 2021)
• ACM/IMS Transactions on Data Science (Special Issue on Data Science for Next-generation Big Data 2021)
• Data Science and Engineering (Special Issue on DASFAA 2020)

Journal Reviewer

• IEEE Transactions on Knowledge and Data Engineering (TKDE)
• ACM Transactions on Information Systems (TOIS)
• IEEE Transactions on Parallel and Distributed Systems (TPDS)
• IEEE Transactions on Computers (TC)
• IEEE Transactions on Intelligent Transportation Systems (TITS)
• ACM/IMS Transactions on Data Science (TDS)

Conferences Program Committee

• ACM International Conference on Management of Data (SIGMOD): 2021, 2023, 2024 (Demo-track)
• PVLDB Review Board: 2019, 2020, 2022, 2023 (Associate Editor), 2024 (Associate Editor), 2025
• IEEE International Conference on Data Engineering (ICDE): 2018, 2019, 2020, 2022, 2023 (Demo Co-chair), 2025
• ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD): 2019, 2020, 2021, 2022, 2025
• IEEE International Conference on Big Data: 2022 (PC Vice-Co-Chair)
• International Joint Conference on Artificial Intelligence (IJCAI): 2018, 2019, 2020
• AAAI Conference on Artificial Intelligence (AAAI): 2019, 2020, 2021, 2022
• ACM Symposium on Cloud Computing (SOCC): 2020
• ACM International Conference on Information and Knowledge Management (CIKM): 2019
• SIAM International Conference on Data Mining (SDM): 2021
• Database Systems for Advanced Applications (DASFAA): 2017, 2018, 2019, 2020, 2021

Teaching Activities

• Computer Architecture, CS Undergraduate
• Database Principles, CS Undergraduate
• Programming Practice and Problem Solving, CS Undergraduate
• English Academic Practice, CS Graduate